Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Location: Houston, TX (Fulltime)

Environment: Standard, 5-days onsite

Must-Have (Technical Expertise & Core Responsibilities)

• Deep Neural Networks (DNN):
• Hands-on experience with CNN, RNN, Graph Neural Networks, and transformers.
• Proficiency in hyperparameter optimization, autoencoders, model evaluation, and error metrics.
• Generative AI:
• Strong knowledge of LLMs (BERT, GPT, etc.), embeddings, and supervised fine-tuning.
• Experience with Reinforcement Learning, RAG (Retrieval-Augmented Generation), and Agentic AI.
• Familiarity with GraphRAG and LLM-as-a-judge architectures.
• Predictive Analytics:
• Expertise in classification, regression, anomaly detection, and sequence modeling.
• Practical application of NLP techniques (sentiment analysis, entity recognition) and knowledge graphs.

Core Responsibilities:

• Design, train, and optimize DNN and generative models for real-world business problems.
• Implement LLM-based solutions (fine-tuning, RAG, agents) to enhance decision-making.
• Develop predictive models for trading, risk assessment, and operational efficiency.
• Collaborate with teams to integrate AI/ML solutions into production systems.
• Rigorously evaluate models using appropriate metrics and error analysis.

Qualifications & Skills:

• Master s/Ph.D. in Computer Science, ML, or related field.
• 5-7+ years of industry experience in applying DNN, generative AI, and predictive analytics.
• Python mastery (TensorFlow/PyTorch, Transformers, Scikit-learn).
• Cloud (AWS) and containerization (Docker) experience.

Nice-to-Have (Preferred Experience):

• Production experience with GenAI models in the energy/commodities trading sector.
• Experience with interactive dashboards (Dash, Streamlit) and time series modeling.
• Knowledge of data orchestrators (Airflow, Dagster) and CI/CD pipelines.